Design parameters to control synthetic gene expression in Escherichia coli

Gene optimization mechanisms: a multi-gene study reveals a high success rate of full-length human proteins expressed in Escherichia coli

The genetic code is universal, but recombinant protein expression in heterologous systems is often hampered by divergent codon usage. Here, we demonstrate that reprogramming by standardized multi-parameter gene optimization software and de novo gene synthesis is a suitable general strategy to improve heterologous protein expression. This study compares expression levels of 94 full-length human wt and sequence-optimized genes coding for pharmaceutically important proteins such as kinases and membrane proteins in E. coli. Fluorescence-based quantification revealed increased protein yields for 70% of in vivo expressed optimized genes compared to the wt DNA sequences and also resulted in increased amounts of protein that can be purified. The improvement in transgene expression correlated with higher mRNA levels in our analyzed examples. In all cases tested, expression levels using wt genes in tRNA-supplemented bacterial strains were outperformed by optimized genes expressed in non-supplemented host cells.

The GeneOptimizer Algorithm: using a sliding window approach to cope with the vast sequence space in multiparameter DNA sequence optimization

One of the main advantages of de novo gene synthesis is the fact that it frees the researcher from any limitations imposed by the use of natural templates. To make the most out of this opportunity, efficient algorithms are needed to calculate a coding sequence, combining different requirements, such as adapted codon usage or avoidance of restriction sites, in the best possible way. We present an algorithm where a “variation window” covering several amino acid positions slides along the coding sequence. Candidate sequences are built comprising the already optimized part of the complete sequence and all possible combinations of synonymous codons representing the amino acids within the window. The candidate sequences are assessed with a quality function, and the first codon of the best candidates’ variation window is fixed. Subsequently the window is shifted by one codon position. As an example of a freely accessible software implementing the algorithm, we present the Mr. Gene web-application. Additionally two experimental applications of the algorithm are shown.

Multifactorial determinants of protein expression in prokaryotic open reading frames

A quantitative description of the relationship between protein expression levels and open reading frame (ORF) nucleotide sequences is important for understanding natural systems, designing synthetic systems, and optimizing heterologous expression. Codon identity, mRNA secondary structure, and nucleotide composition within ORFs markedly influence expression levels. Bioinformatic analysis of ORF sequences in 816 bacterial genomes revealed that these features show distinct regional trends. To investigate their effects on protein expression, we designed 285 synthetic genes and determined corresponding expression levels in vitro using Escherichia coli extracts. We developed a mathematical function, parameterized using this synthetic gene data set, which enables computation of protein expression levels from ORF nucleotide sequences. In addition to its practical application in the design of heterologous expression systems, this equation provides mechanistic insight into the factors that control translation efficiency. We found that expression is strongly dependent on the presence of high AU content and low secondary structure in the ORF 5' region. Choice of high-frequency codons contributes to a lesser extent. The 3' terminal AU content makes modest, but detectable contributions. We present a model for the effect of these factors on the three phases of ribosomal function: initiation, elongation, and termination.

New insights into the de novo gene synthesis using the automatic kinetics switch approach

Here we present a simple, highly efficient, universal automatic kinetics switch (AKS) gene synthesis method that enables synthesis of DNA up to 1.6kbp from 1nM oligonucleotide with just one polymerase chain reaction (PCR) process. This method eliminates the interference between the PCR assembly and amplification in one-step gene synthesis and simultaneously maximizes the amplification of emerged desired DNA by using a pair of flanked primers. In addition, we describe an analytical model of PCR gene synthesis based on the thermodynamics and kinetics of DNA hybridization. The kinetics difference between standard PCR amplification and one-step PCR gene synthesis is analyzed using this model and is validated using real-time gene synthesis with eight gene segments (318-1656bp). The effects of oligonucleotide concentration, stringency of annealing temperature, annealing time, extension time, and PCR buffer conditions are examined systematically. Analysis of the experimental results leads to new insights into the gene synthesis process and aids in optimizing gene synthesis conditions. We further extend this method for multiplexing gene assembly with a total DNA length up to 5.74kbp from 1nM oligonucleotide.

All-codon scanning identifies p53 cancer rescue mutations

In vitro scanning mutagenesis strategies are valuable tools to identify critical residues in proteins and to generate proteins with modified properties. We describe the fast and simple All-Codon Scanning (ACS) strategy that creates a defined gene library wherein each individual codon within a specific target region is changed into all possible codons with only a single codon change per mutagenesis product. ACS is based on a multiplexed overlapping mutagenesis primer design that saturates only the targeted gene region with single codon changes. We have used ACS to produce single amino-acid changes in small and large regions of the human tumor suppressor protein p53 to identify single amino-acid substitutions that can restore activity to inactive p53 found in human cancers. Single-tube reactions were used to saturate defined 30-nt regions with all possible codon changes. The same technique was used in 20 parallel reactions to scan the 600-bp fragment encoding the entire p53 core domain. Identification of several novel p53 cancer rescue mutations demonstrated the utility of the ACS approach. ACS is a fast, simple and versatile method, which is useful for protein structure–function analyses and protein design or evolution problems.

GeneDesign 3.0 is an updated synthetic biology toolkit

GeneDesign is a set of web applications that provides public access to a nucleotide manipulation pipeline for synthetic biology. The server is public and freely accessible, and the source is available for download under the New BSD License. Since GeneDesign was published and made publicly available 3 years ago, we have made its code base more efficient, added several algorithms and modules, updated the restriction enzyme library, added batch processing capabilities, and added several command line modules, all of which we briefly describe here.

Production of recombinant proteins from protozoan parasites

Although the past decade has witnessed sequencing from an increasing number of parasites, modern high-throughput DNA sequencing technologies have the potential to generate complete genome sequences at even higher rates. Along with the discovery of genes that might constitute potential targets for chemotherapy or vaccination, the need for novel protein expression platforms has become a pressing matter. In addition to reviewing the advantages and limitations of the currently available and emerging expression systems, we discuss novel approaches that could overcome current limitations, including the 'pseudoparasite' concept, an expression platform in which the choice of the surrogate organism is based on its phylogenetic affinity to the target parasite, while taking advantage of the whole engineered organism as a vaccination adjuvant.

On relevance of codon usage to expression of synthetic and natural genes in Escherichia coli

A recent investigation concluded that codon bias did not affect expression of green fluorescent protein (GFP) variants in Escherichia coli, while stability of an mRNA secondary structure near the 5' end played a dominant role. We demonstrate that combining the two variables using regression trees or support vector regression yields a biologically plausible model with better support in the GFP data set and in other experimental data: codon usage is relevant for protein levels if the 5' mRNA structures are not strong. Natural E. coli genes had weaker 5' mRNA structures than the examined set of GFP variants and did not exhibit a correlation between the folding free energy of 5' mRNA structures and protein expression.

Strategies for protein synthetic biology

Proteins are the most versatile among the various biological building blocks and a mature field of protein engineering has lead to many industrial and biomedical applications. But the strength of proteins—their versatility, dynamics and interactions—also complicates and hinders systems engineering. Therefore, the design of more sophisticated, multi-component protein systems appears to lag behind, in particular, when compared to the engineering of gene regulatory networks. Yet, synthetic biologists have started to tinker with the information flow through natural signaling networks or integrated protein switches. A successful strategy common to most of these experiments is their focus on modular interactions between protein domains or domains and peptide motifs. Such modular interaction swapping has rewired signaling in yeast, put mammalian cell morphology under the control of light, or increased the flux through a synthetic metabolic pathway. Based on this experience, we outline an engineering framework for the connection of reusable protein interaction devices into self-sufficient circuits. Such a framework should help to ‘refacture’ protein complexity into well-defined exchangeable devices for predictive engineering. We review the foundations and initial success stories of protein synthetic biology and discuss the challenges and promises on the way from protein- to protein systems design.

Translation efficiency is determined by both codon bias and folding energy

Synonymous mutations do not alter the protein produced yet can have a significant effect on protein levels. The mechanisms by which this effect is achieved are controversial; although some previous studies have suggested that codon bias is the most important determinant of translation efficiency, a recent study suggested that mRNA folding at the beginning of genes is the dominant factor via its effect on translation initiation. Using the Escherichia coli and Saccharomyces cerevisiae transcriptomes, we conducted a genome-scale study aiming at dissecting the determinants of translation efficiency. There is a significant association between codon bias and translation efficiency across all endogenous genes in E. coli and S. cerevisiae but no association between folding energy and translation efficiency, demonstrating the role of codon bias as an important determinant of translation efficiency. However, folding energy does modulate the strength of association between codon bias and translation efficiency, which is maximized at very weak mRNA folding (i.e., high folding energy) levels. We find a strong correlation between the genomic profiles of ribosomal density and genomic profiles of folding energy across mRNA, suggesting that lower folding energies slow down the ribosomes and decrease translation efficiency. Accordingly, we find that selection forces act near uniformly to decrease the folding energy at the beginning of genes. In summary, these findings testify that in endogenous genes, folding energy affects translation efficiency in a global manner that is not related to the expression levels of individual genes, and thus cannot be detected by correlation with their expression levels.

Functional viral metagenomics and the next generation of molecular tools

The enzymes of bacteriophages and other viruses have been essential research tools since the first days of molecular biology. However, the current repertoire of viral enzymes only hints at their overall potential. The most commonly used enzymes are derived from a surprisingly small number of cultivated viruses, which is remarkable considering the extreme abundance and diversity of viruses revealed over the past decade by metagenomic analysis. To access the treasure trove of enzymes hidden in the global virosphere and develop them for research, therapeutic and diagnostic uses, improvements are needed in our ability to rapidly and efficiently discover, express and characterize viral genes to produce useful proteins. In this paper, we discuss improvements to sampling and cloning methods, functional and genomics-based screens, and expression systems, which should accelerate discovery of new enzymes and other viral proteins for use in research and medicine.